TY - GEN
T1 - Cross analytics of student and course activities from e-book operation logs
AU - Shimada, Atsushi
AU - Konomi, Shinichi
N1 - Publisher Copyright:
© 2017 Asia-Pacific Society for Computers in Education. All rights reserved.
PY - 2017
Y1 - 2017
N2 - In this paper, we propose a cross analytics methodology of student activities and course activities using e-Book operation logs collected in 15 courses with face-to-face lecture style over 4 weeks. These courses commonly use the same lecture materials, but are conducted by different teachers. The new aspect of our research is that we perform cross analysis over courses. Most past researches focus on students' activities in a specific course, and give discussions about how the students behaved, how the behaviors differ from each other. In contrast, our research focuses on the course activities and conducts a comparison among courses. First, we begin with data alignment for row data to rectify a student activity every 10 seconds. Through our analytics, it becomes clear that whether students' activities varies with teachers or their teaching styles. In the experiments, we applied the proposed analytics to 1.1-million operation logs, and found out interesting characteristics through the comparison across courses.
AB - In this paper, we propose a cross analytics methodology of student activities and course activities using e-Book operation logs collected in 15 courses with face-to-face lecture style over 4 weeks. These courses commonly use the same lecture materials, but are conducted by different teachers. The new aspect of our research is that we perform cross analysis over courses. Most past researches focus on students' activities in a specific course, and give discussions about how the students behaved, how the behaviors differ from each other. In contrast, our research focuses on the course activities and conducts a comparison among courses. First, we begin with data alignment for row data to rectify a student activity every 10 seconds. Through our analytics, it becomes clear that whether students' activities varies with teachers or their teaching styles. In the experiments, we applied the proposed analytics to 1.1-million operation logs, and found out interesting characteristics through the comparison across courses.
UR - http://www.scopus.com/inward/record.url?scp=85053925158&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:85053925158
SN - 9789869401265
T3 - Proceedings of the 25th International Conference on Computers in Education, ICCE 2017 - Main Conference Proceedings
SP - 433
EP - 438
BT - Proceedings of the 25th International Conference on Computers in Education, ICCE 2017 - Main Conference Proceedings
A2 - Mohd Ayub, Ahmad Fauzi
A2 - Mitrovic, Antonija
A2 - Yang, Jie-Chi
A2 - Wong, Su Luan
A2 - Chen, Wenli
PB - Asia-Pacific Society for Computers in Education
T2 - 25th International Conference on Computers in Education, ICCE 2017
Y2 - 4 December 2017 through 8 December 2017
ER -